function sensor_data = kspaceFirstOrder1D(kgrid, medium, source, sensor, varargin)
%KSPACEFIRSTORDER1D 1D time-domain simulation of wave propagation.
%
% DESCRIPTION:
%     kspaceFirstOrder1D simulates the time-domain propagation of
%     compressional waves through a one-dimensional homogeneous or
%     heterogeneous acoustic medium given four input structures: kgrid,
%     medium, source, and sensor. The computation is based on a first-order
%     k-space model which accounts for power law absorption and a
%     heterogeneous sound speed and density. If medium.BonA is specified,
%     cumulative nonlinear effects are also modelled. At each time-step
%     (defined by kgrid.dt and kgrid.Nt or kgrid.t_array), the acoustic
%     field parameters at the positions defined by sensor.mask are recorded
%     and stored. If kgrid.t_array is set to 'auto', this array is
%     automatically generated using the makeTime method of the kWaveGrid
%     class. An anisotropic absorbing boundary layer called a perfectly
%     matched layer (PML) is implemented to prevent waves that leave one
%     side of the domain being reintroduced from the opposite side (a
%     consequence of using the FFT to compute the spatial derivatives in
%     the wave equation). This allows infinite domain simulations to be
%     computed using small computational grids.
%
%     For a homogeneous medium the formulation is exact and the time-steps
%     are only limited by the effectiveness of the perfectly matched layer.
%     For a heterogeneous medium, the solution represents a leap-frog
%     pseudospectral method with a k-space correction that improves the
%     accuracy of computing the temporal derivatives. This allows larger
%     time-steps to be taken for the same level of accuracy compared to
%     conventional pseudospectral time-domain methods. The computational
%     grids are staggered both spatially and temporally.
%
%     An initial pressure distribution can be specified by assigning a
%     matrix (the same size as the computational grid) of arbitrary numeric
%     values to source.p0. A time varying pressure source can similarly be
%     specified by assigning a binary matrix (i.e., a matrix of 1's and 0's
%     with the same dimensions as the computational grid) to source.p_mask
%     where the 1's represent the grid points that form part of the source.
%     The time varying input signals are then assigned to source.p. This
%     can be a single time series (in which case it is applied to all
%     source elements), or a matrix of time series following the source
%     elements using MATLAB's standard column-wise linear matrix index
%     ordering. A time varying velocity source can be specified in an
%     analogous fashion, where the source location is specified by
%     source.u_mask, and the time varying input velocity is assigned to
%     source.ux.
%
%     The field values are returned as arrays of time series at the sensor
%     locations defined by sensor.mask. This can be defined in three
%     different ways. (1) As a binary matrix (i.e., a matrix of 1's and 0's
%     with the same dimensions as the computational grid) representing the
%     grid points within the computational grid that will collect the data.
%     (2) As the grid coordinates of two opposing ends of a line in the
%     form [x1; x2]. This is equivalent to using a binary sensor mask
%     covering the same region, however, the output is indexed differently
%     as discussed below. (3) As a series of Cartesian coordinates within
%     the grid which specify the location of the pressure values stored at
%     each time step. If the Cartesian coordinates don't exactly match the
%     coordinates of a grid point, the output values are calculated via
%     interpolation. The Cartesian points must be given as a 1 by N matrix
%     corresponding to the x positions, where the Cartesian origin is
%     assumed to be in the center of the grid. If no output is required,
%     the sensor input can be replaced with an empty array [].
%
%     If sensor.mask is given as a set of Cartesian coordinates, the
%     computed sensor_data is returned in the same order. If sensor.mask is
%     given as a binary matrix, sensor_data is returned using MATLAB's
%     standard column-wise linear matrix index ordering. In both cases, the
%     recorded data is indexed as sensor_data(sensor_point_index,
%     time_index). For a binary sensor mask, the field values at a
%     particular time can be restored to the sensor positions within the
%     computation grid using unmaskSensorData. If sensor.mask is given as a
%     list of opposing ends of a line, the recorded data is indexed as
%     sensor_data(line_index).p(x_index, time_index), where x_index
%     corresponds to the grid index within the line, and line_index
%     corresponds to the number of lines if more than one is specified.
%
%     By default, the recorded acoustic pressure field is passed directly
%     to the output sensor_data. However, other acoustic parameters can
%     also be recorded by setting sensor.record to a cell array of the form
%     {'p', 'u', 'p_max', ...}. For example, both the particle velocity and
%     the acoustic pressure can be returned by setting sensor.record =
%     {'p', 'u'}. If sensor.record is given, the output sensor_data is
%     returned as a structure with the different outputs appended as
%     structure fields. For example, if sensor.record = {'p', 'p_final',
%     'p_max', 'u'}, the output would contain fields sensor_data.p,
%     sensor_data.p_final, sensor_data.p_max, and sensor_data.ux. Most of
%     the output parameters are recorded at the given sensor positions and
%     are indexed as sensor_data.field(sensor_point_index, time_index) or
%     sensor_data(line_index).field(x_index, time_index) if using a sensor
%     mask defined as opposing ends of a line. The exceptions are the
%     averaged quantities ('p_max', 'p_rms', 'u_max', 'p_rms', 'I_avg'),
%     the 'all' quantities ('p_max_all', 'p_min_all', 'u_max_all',
%     'u_min_all'), and the final quantities ('p_final', 'u_final'). The
%     averaged quantities are indexed as
%     sensor_data.p_max(sensor_point_index) or
%     sensor_data(line_index).p_max(x_index) if using line ends, while the
%     final and 'all' quantities are returned over the entire grid and are
%     always indexed as sensor_data.p_final(nx), regardless of the type of
%     sensor mask.
%
%     kspaceFirstOrder1D may also be used for time reversal image
%     reconstruction by assigning the time varying pressure recorded over
%     an arbitrary sensor surface to the input field
%     sensor.time_reversal_boundary_data. This data is then enforced in
%     time reversed order as a time varying Dirichlet boundary condition
%     over the sensor surface given by sensor.mask. The boundary data must
%     be indexed as sensor.time_reversal_boundary_data(sensor_point_index,
%     time_index). If sensor.mask is given as a set of Cartesian
%     coordinates, the boundary data must be given in the same order. An
%     equivalent binary sensor mask (computed using nearest neighbour
%     interpolation) is then used to place the pressure values into the
%     computational grid at each time step. If sensor.mask is given as a
%     binary matrix of sensor points, the boundary data must be ordered
%     using MATLAB's standard column-wise linear matrix indexing. If no
%     additional inputs are required, the source input can be replaced with
%     an empty array [].
%
%     Acoustic attenuation compensation can also be included during time
%     reversal image reconstruction by assigning the absorption parameters
%     medium.alpha_coeff and medium.alpha_power and reversing the sign of
%     the absorption term by setting medium.alpha_sign = [-1, 1]. This
%     forces the propagating waves to grow according to the absorption
%     parameters instead of decay. The reconstruction should then be
%     regularised by assigning a filter to medium.alpha_filter (this can be
%     created using getAlphaFilter).
%
%     Note: To run a simple photoacoustic image reconstruction example
%     using time reversal (that commits the 'inverse crime' of using the
%     same numerical parameters and model for data simulation and image
%     reconstruction), the sensor_data returned from a k-Wave simulation
%     can be passed directly to sensor.time_reversal_boundary_data with the
%     input fields source.p0 and source.p removed or set to zero.
%
% USAGE:
%     sensor_data = kspaceFirstOrder1D(kgrid, medium, source, sensor)
%     sensor_data = kspaceFirstOrder1D(kgrid, medium, source, sensor, ...) 
%
% INPUTS:
% The minimum fields that must be assigned to run an initial value problem
% (for example, a photoacoustic forward simulation) are marked with a *. 
%
%     kgrid*                 - k-Wave grid object returned by kWaveGrid
%                              containing Cartesian and k-space grid fields 
%     kgrid.t_array*         - evenly spaced array of time values [s] (set
%                              to 'auto' by kWaveGrid) 
%
%
%     medium.sound_speed*    - sound speed distribution within the acoustic
%                              medium [m/s] 
%     medium.sound_speed_ref - reference sound speed used within the
%                              k-space operator (phase correction term)
%                              [m/s]
%     medium.density*        - density distribution within the acoustic
%                              medium [kg/m^3] 
%     medium.BonA            - parameter of nonlinearity
%     medium.alpha_power     - power law absorption exponent
%     medium.alpha_coeff     - power law absorption coefficient 
%                              [dB/(MHz^y cm)] 
%     medium.alpha_mode      - optional input to force either the
%                              absorption or dispersion terms in the
%                              equation of state to be excluded; valid
%                              inputs are 'no_absorption' or
%                              'no_dispersion'  
%     medium.alpha_filter    - frequency domain filter applied to the
%                              absorption and dispersion terms in the
%                              equation of state 
%     medium.alpha_sign      - two element array used to control the sign
%                              of absorption and dispersion terms in the
%                              equation of state  
%
%
%     source.p0*             - initial pressure within the acoustic medium
%     source.p               - time varying pressure at each of the source
%                              positions given by source.p_mask 
%     source.p_mask          - binary matrix specifying the positions of
%                              the time varying pressure source
%                              distribution 
%     source.p_mode          - optional input to control whether the input
%                              pressure is injected as a mass source or
%                              enforced as a dirichlet boundary condition;
%                              valid inputs are 'additive' (the default) or
%                              'dirichlet'    
%     source.ux              - time varying particle velocity in the
%                              x-direction at each of the source positions
%                              given by source.u_mask 
%     source.u_mask          - binary matrix specifying the positions of
%                              the time varying particle velocity
%                              distribution
%     source.u_mode          - optional input to control whether the input
%                              velocity is applied as a force source or
%                              enforced as a dirichlet boundary condition;
%                              valid inputs are 'additive' (the default) or
%                              'dirichlet'
%
%
%     sensor.mask*           - binary matrix or a set of Cartesian points
%                              where the pressure is recorded at each
%                              time-step  
%     sensor.record          - cell array of the acoustic parameters to
%                              record in the form sensor.record = {'p',
%                                'u', ...}; valid inputs are:  
%                                'p' (acoustic pressure)
%                                'p_max' (maximum pressure)
%                                'p_min' (minimum pressure)
%                                'p_rms' (RMS pressure)
%                                'p_final' (final pressure field at all grid points)
%                                'p_max_all' (maximum pressure at all grid points)
%                                'p_min_all' (minimum pressure at all grid points)
%                                'u' (particle velocity)
%                                'u_max' (maximum particle velocity)
%                                'u_min' (minimum particle velocity)
%                                'u_rms' (RMS particle velocity)
%                                'u_final' (final particle velocity field at all grid points)
%                                'u_max_all' (maximum particle velocity at all grid points)
%                                'u_min_all' (minimum particle velocity at all grid points)
%                                'u_non_staggered' (particle velocity on non-staggered grid)
%                                'I' (time varying acoustic intensity)
%                                'I_avg' (average acoustic intensity) 
%     sensor.record_start_index 
%                            - time index at which the sensor should start
%                              recording the data specified by 
%                              sensor.record (default = 1) 
%     sensor.time_reversal_boundary_data 
%                            - time varying pressure enforced as a
%                              Dirichlet boundary condition over
%                              sensor.mask
%     sensor.frequency_response 
%                            - two element array specifying the center
%                              frequency and percentage bandwidth of a
%                              frequency domain Gaussian filter applied to
%                              the sensor_data
%
% Note: For heterogeneous medium parameters, medium.sound_speed and
% medium.density must be given in matrix form with the same dimensions as
% kgrid. For homogeneous medium parameters, these can be given as single
% numeric values. If the medium is homogeneous and velocity inputs or
% outputs are not required, it is not necessary to specify medium.density.
%
% OPTIONAL INPUTS:
%     Optional 'string', value pairs that may be used to modify the default
%     computational settings. 
%
%     'CartInterp'           - Interpolation mode used to extract the
%                              pressure when a Cartesian sensor mask is
%                              given. If set to 'nearest' and more than one
%                              Cartesian point maps to the same grid point,
%                              duplicated data points are discarded and
%                              sensor_data will be returned with less
%                              points than that specified by sensor.mask
%                              (default = 'linear').  
%     'CreateLog'            - Boolean controlling whether the command line
%                              output is saved using the diary function
%                              with a date and time stamped filename
%                              (default = false).
%     'DataCast'             - String input of the data type that variables
%                              are cast to before computation. For example,
%                              setting to 'single' will speed up the
%                              computation time (due to the improved
%                              efficiency of fftn and ifftn for this data
%                              type) at the expense of a loss in precision. 
%                              This variable is also useful for utilising
%                              GPU parallelisation through libraries such
%                              as the Parallel Computing Toolbox by setting
%                              'DataCast' to 'gpuArray-single' (default =
%                              'off').
%     'DataRecast'           - Boolean controlling whether the output data
%                              is cast back to double precision. If set to
%                              false, sensor_data will be returned in the
%                              data format set using the 'DataCast' option.
%     'DisplayMask'          - Binary matrix overlaid onto the animated
%                              simulation display. Elements set to 1 within
%                              the display mask are set to black within the
%                              display (default = sensor.mask).
%     'LogScale'             - Boolean controlling whether the pressure
%                              field is log compressed before display
%                              (default = false). The data is compressed by
%                              scaling both the positive and negative
%                              values between 0 and 1 (truncating the data
%                              to the given plot scale), adding a scalar
%                              value (compression factor) and then using
%                              the corresponding portion of a log10 plot
%                              for the compression (the negative parts are
%                              remapped to be negative thus the default
%                              color scale will appear unchanged). The
%                              amount of compression can be controlled by
%                              adjusting the compression factor which can
%                              be given in place of the Boolean input. The
%                              closer the compression factor is to zero,
%                              the steeper the corresponding part of the 
%                              log10 plot used, and the greater the
%                              compression (the default compression factor
%                              is 0.02).
%     'MovieArgs'            - Settings for VideoWriter. Parameters must be
%                              given as {'param', value, ...} pairs within
%                              a cell array (default = {}), where 'param'
%                              corresponds to a writable property of a
%                              VideoWriter object. 
%     'MovieName'            - Name of the movie produced when
%                              'RecordMovie' is set to true (default =
%                              'date-time-kspaceFirstOrder1D'). 
%     'MovieProfile'         - Profile input passed to VideoWriter.
%     'PlotFreq'             - The number of iterations which must pass 
%                              before the simulation plot is updated
%                              (default = 10).
%     'PlotLayout'           - Boolean controlling whether a four panel
%                              plot of the initial simulation layout is
%                              produced (initial pressure, sensor mask,
%                              sound speed, density) (default = false).
%     'PlotPML'              - Boolean controlling whether the perfectly
%                              matched layer is shown in the simulation
%                              plots. If set to false, the PML is not
%                              displayed (default = true). 
%     'PlotScale'            - [min, max] values used to control the
%                              scaling for imagesc (visualisation). If set
%                              to 'auto', a symmetric plot scale is chosen
%                              automatically for each plot frame.
%     'PlotSim'              - Boolean controlling whether the simulation
%                              iterations are progressively plotted
%                              (default = true). 
%     'PMLAlpha'             - Absorption within the perfectly matched 
%                              layer in Nepers per grid point (default =
%                              2).
%     'PMLInside'            - Boolean controlling whether the perfectly 
%                              matched layer is inside or outside the grid.
%                              If set to false, the input grids are
%                              enlarged by PMLSize before running the
%                              simulation (default = true).
%     'PMLSize'              - Size of the perfectly matched layer in grid
%                              points. To remove the PML, set the
%                              appropriate PMLAlpha to zero rather than
%                              forcing the PML to be of zero size (default
%                              = 20).
%     'RecordMovie'          - Boolean controlling whether the displayed
%                              image frames are captured and stored as a
%                              movie using VideoWriter (default = false).
%     'Smooth'               - Boolean controlling whether source.p0,
%                              medium.sound_speed, and medium.density are
%                              smoothed using smooth before computation.
%                              'Smooth' can either be given as a single
%                              Boolean value or as a 3 element array to
%                              control the smoothing of source.p0,
%                              medium.sound_speed, and medium.density,
%                              independently (default = [true, false,
%                              false]).
%
% OUTPUTS:
% If sensor.record is not defined by the user:
%     sensor_data            - time varying pressure recorded at the sensor
%                              positions given by sensor.mask
%
% If sensor.record is defined by the user:
%     sensor_data.p          - time varying pressure recorded at the sensor
%                              positions given by sensor.mask (returned if
%                              'p' is set)
%     sensor_data.p_max      - maximum pressure recorded at the sensor
%                              positions given by sensor.mask (returned if
%                              'p_max' is set)  
%     sensor_data.p_min      - minimum pressure recorded at the sensor
%                              positions given by sensor.mask (returned if
%                              'p_min' is set)  
%     sensor_data.p_rms      - rms of the time varying pressure recorded at
%                              the sensor positions given by sensor.mask
%                              (returned if 'p_rms' is set)
%     sensor_data.p_final    - final pressure field at all grid points
%                              within the domain (returned if 'p_final' is
%                              set)
%     sensor_data.p_max_all  - maximum pressure recorded at all grid points
%                              within the domain (returned if 'p_max_all'
%                              is set) 
%     sensor_data.p_min_all  - minimum pressure recorded at all grid points
%                              within the domain (returned if 'p_min_all'
%                              is set)
%     sensor_data.ux         - time varying particle velocity in the
%                              x-direction recorded at the sensor positions
%                              given by sensor.mask (returned if 'u' is
%                              set) 
%     sensor_data.ux_max     - maximum particle velocity in the x-direction
%                              recorded at the sensor positions given by
%                              sensor.mask (returned if 'u_max' is set)   
%     sensor_data.ux_min     - minimum particle velocity in the x-direction
%                              recorded at the sensor positions given by
%                              sensor.mask (returned if 'u_min' is set)   
%     sensor_data.ux_rms     - rms of the time varying particle velocity in
%                              the x-direction recorded at the sensor
%                              positions given by sensor.mask (returned if
%                              'u_rms' is set)     
%     sensor_data.ux_final   - final particle velocity field in the
%                              x-direction at all grid points within the
%                              domain (returned if 'u_final' is set) 
%     sensor_data.ux_max_all - maximum particle velocity in the x-direction
%                              recorded at all grid points within the
%                              domain (returned if 'u_max_all' is set)
%     sensor_data.ux_min_all - minimum particle velocity in the x-direction
%                              recorded at all grid points within the
%                              domain (returned if 'u_min_all' is set)   
%     sensor_data.ux_non_staggered 
%                            - time varying particle velocity in the
%                              x-direction recorded at the sensor positions
%                              given by sensor.mask after shifting to the
%                              non-staggered grid (returned if
%                              'u_non_staggered' is set)
%     sensor_data.Ix         - time varying acoustic intensity in the
%                              x-direction recorded at the sensor positions
%                              given by sensor.mask (returned if 'I' is
%                              set)
%     sensor_data.Ix_avg     - average acoustic intensity in the
%                              x-direction recorded at the sensor positions
%                              given by sensor.mask (returned if 'I_avg' is
%                              set)
%
% ABOUT:
%     author                 - Bradley Treeby and Ben Cox
%     date                   - 22nd April 2009
%     last update            - 25th July 2019
%       
% This function is part of the k-Wave Toolbox (http://www.k-wave.org)
% Copyright (C) 2009-2019 Bradley Treeby and Ben Cox
%
% See also kspaceFirstOrderAS, kspaceFirstOrder2D, kspaceFirstOrder3D,
% kWaveGrid, kspaceSecondOrder

% This file is part of k-Wave. k-Wave is free software: you can
% redistribute it and/or modify it under the terms of the GNU Lesser
% General Public License as published by the Free Software Foundation,
% either version 3 of the License, or (at your option) any later version.
% 
% k-Wave is distributed in the hope that it will be useful, but WITHOUT ANY
% WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
% FOR A PARTICULAR PURPOSE.  See the GNU Lesser General Public License for
% more details. 
% 
% You should have received a copy of the GNU Lesser General Public License
% along with k-Wave. If not, see <http://www.gnu.org/licenses/>.

% suppress mlint warnings that arise from using sub-scripts
%#ok<*NASGU>
%#ok<*COLND>
%#ok<*NODEF>
%#ok<*INUSL>

% =========================================================================
% CHECK INPUT STRUCTURES AND OPTIONAL INPUTS
% =========================================================================

% start the timer and store the start time
start_time = clock;
tic;

% set the name of the simulation code
MFILE = mfilename;

% get the number of inputs and outputs (nargin and nargout can't be used in
% subscripts in MATLAB 2016b or later)
num_inputs  = nargin;
num_outputs = nargout;

% run subscript to check inputs
kspaceFirstOrder_inputChecking;

% =========================================================================
% CALCULATE MEDIUM PROPERTIES ON STAGGERED GRID
% =========================================================================

% interpolate the values of the density at the staggered grid locations
% where sgx = (x + dx/2)
if numel(rho0) > 1 && flags.use_sg
    
    % rho0 is heterogeneous and staggered grids are used
    rho0_sgx = interp1(kgrid.x, rho0, kgrid.x + kgrid.dx/2, '*linear');
    
    % set values outside of the interpolation range to original values 
    rho0_sgx(isnan(rho0_sgx)) = rho0(isnan(rho0_sgx)); 
    
else
    % rho0 is homogeneous or staggered grids are not used
    rho0_sgx = rho0;
end

% invert rho0 so it doesn't have to be done each time step
rho0_sgx_inv = 1./rho0_sgx;

% clear unused variables
clear rho0_sgx

% =========================================================================
% PREPARE DERIVATIVE AND PML OPERATORS
% =========================================================================

% get the PML operators based on the reference sound speed and PML settings
pml_x     = getPML(kgrid.Nx, kgrid.dx, kgrid.dt, c_ref, pml_x_size, pml_x_alpha, false, 1);
pml_x_sgx = getPML(kgrid.Nx, kgrid.dx, kgrid.dt, c_ref, pml_x_size, pml_x_alpha, true && flags.use_sg, 1);

% define the k-space derivative operator
ddx_k = ifftshift(1i * kgrid.kx_vec);

% define the staggered grid shift operators (the option flags.use_sg exists for
% debugging)
if flags.use_sg
    shift_pos = ifftshift( exp( 1i * kgrid.kx_vec * kgrid.dx/2) );
    shift_neg = ifftshift( exp(-1i * kgrid.kx_vec * kgrid.dx/2) );
else
    shift_pos = 1;
    shift_neg = 1;
end

% create k-space operator (the option flags.use_kspace exists for debugging)
if flags.use_kspace
    kappa        = ifftshift(sinc(c_ref .* kgrid.k .* kgrid.dt / 2));
    if (flags.source_p && strcmp(source.p_mode, 'additive')) || (flags.source_ux && strcmp(source.u_mode, 'additive'))
        source_kappa = ifftshift(cos (c_ref .* kgrid.k .* kgrid.dt / 2));
    end
else
    kappa        = 1;
    source_kappa = 1;
end

% =========================================================================
% DATA CASTING
% =========================================================================

% preallocate the loop variables using the castZeros anonymous function
% (this creates a matrix of zeros in the data type specified by data_cast)
p      = castZeros([kgrid.Nx, 1]);
rhox   = castZeros([kgrid.Nx, 1]);
ux_sgx = castZeros([kgrid.Nx, 1]);
p_k    = castZeros([kgrid.Nx, 1]);

% run subscript to cast the remaining loop variables to the data type
% specified by data_cast 
if ~strcmp(data_cast, 'off')
    kspaceFirstOrder_dataCast;
end

% =========================================================================
% CREATE INDEX VARIABLES
% =========================================================================

% setup the time index variable
if ~flags.time_rev
    index_start = 1;
    index_step = 1;
    index_end = kgrid.Nt;  
else
    
    % reverse the order of the input data
    sensor.time_reversal_boundary_data = fliplr(sensor.time_reversal_boundary_data);    
    index_start = 1;
    index_step = 1;

    % stop one time point before the end so the last points are not
    % propagated
    index_end = kgrid.Nt - 1;      
    
end

% =========================================================================
% PREPARE VISUALISATIONS
% =========================================================================

% pre-compute suitable axes scaling factor
if flags.plot_layout || flags.plot_sim
    [x_sc, scale, prefix] = scaleSI(max(kgrid.x));  %#ok<ASGLU>
end

% run subscript to plot the simulation layout if 'PlotLayout' is set to true
if flags.plot_layout
    kspaceFirstOrder_plotLayout;
end

% initialise the figure used for animation if 'PlotSim' is set to 'true'
if flags.plot_sim
    kspaceFirstOrder_initialiseFigureWindow;
end  

% initialise movie parameters if 'RecordMovie' is set to 'true'
if flags.record_movie
    kspaceFirstOrder_initialiseMovieParameters;
end

% =========================================================================
% LOOP THROUGH TIME STEPS
% =========================================================================

% update command line status
disp(['  precomputation completed in ' scaleTime(toc)]);
disp('  starting time loop...');

% restart timing variables
loop_start_time = clock;
tic;

% start time loop
for t_index = index_start:index_step:index_end
    
    % enforce time reversal bounday condition
    if flags.time_rev   
        
        % load pressure value and enforce as a Dirichlet boundary condition
        p(sensor_mask_index) = sensor.time_reversal_boundary_data(:, t_index);

        % update p_k
        p_k = fft(p);

        % compute rhox using an adiabatic equation of state
        rhox_mod = p ./ (c0.^2);
        rhox(sensor_mask_index) = rhox_mod(sensor_mask_index);
        
    end   
    
    % calculate ux at the next time step using dp/dx at the current time
    % step
    if ~flags.nonuniform_grid && ~flags.use_finite_difference
        
        % calculate gradient using the k-space method on a regular grid
        ux_sgx = pml_x_sgx .* (  pml_x_sgx .* ux_sgx - dt .* rho0_sgx_inv .* real(ifft(ddx_k .* shift_pos .* kappa .* p_k))  );
        
    elseif flags.use_finite_difference
        switch flags.use_finite_difference
            case 2
                
                % calculate gradient using second-order accurate finite
                % difference scheme (including half step forward)
                dpdx = ([p(2:end); 0] - p) / kgrid.dx;    
                ux_sgx = pml_x_sgx .* (  pml_x_sgx .* ux_sgx - dt .* rho0_sgx_inv .* dpdx );
                
            case 4
                
                % calculate gradient using fourth-order accurate finite
                % difference scheme (including half step forward)
                dpdx = ([0; p(1:(end-1))] - 27*p + 27*[p(2:end); 0] - [p(3:end); 0; 0])/(24*kgrid.dx);
                ux_sgx = pml_x_sgx .* (  pml_x_sgx .* ux_sgx - dt .* rho0_sgx_inv .* dpdx );
                
        end 
    else
        
        % calculate gradient using the k-space method on a non-uniform grid
        % via the mapped pseudospectral method         
        ux_sgx = pml_x_sgx .* (  pml_x_sgx .* ux_sgx - dt .* rho0_sgx_inv .* kgrid.dxudxn_sgx .* real(ifft(ddx_k .* shift_pos .* kappa .* p_k))  );
        
    end    
    
    % add in the velocity source term
    if flags.source_ux >= t_index
        switch source.u_mode
            case 'dirichlet'
            
                % enforce the source values as a dirichlet boundary condition
                ux_sgx(u_source_pos_index) = source.ux(u_source_sig_index, t_index);
            
            case 'additive'
                
                % extract the source values into a matrix
                source_mat = castZeros([kgrid.Nx, 1]);
                source_mat(u_source_pos_index) = source.ux(u_source_sig_index, t_index);

                % apply the k-space correction
                source_mat = real(ifft(source_kappa .* fft(source_mat)));

                % add the source values to the existing field values
                % including the k-space correction
                ux_sgx = ux_sgx + source_mat;
                
            case 'additive-no-correction'
            
                % add the source values to the existing field values        
                ux_sgx(u_source_pos_index) = ux_sgx(u_source_pos_index) + source.ux(u_source_sig_index, t_index);
            
        end
    end    

    % calculate du/dx at the next time step
    if ~flags.nonuniform_grid && ~flags.use_finite_difference
        
        % calculate gradient using the k-space method on a regular grid  
        duxdx = real(ifft(ddx_k .* shift_neg .* kappa .* fft(ux_sgx)));   

    elseif flags.use_finite_difference
        switch flags.use_finite_difference
            case 2
                
                % calculate gradient using second-order accurate finite
                % difference scheme (including half step backward)
                duxdx = (ux_sgx - [0; ux_sgx(1:end - 1)]) / kgrid.dx;
                
            case 4
                
                % calculate gradient using fourth-order accurate finite
                % difference scheme (including half step backward)
                duxdx = ([0; 0; ux_sgx(1:(end - 2))] - 27 * [0; ux_sgx(1:(end - 1))] + 27 * ux_sgx -[ux_sgx(2:end); 0]) / (24 * kgrid.dx);
                
        end 
    else        
        
        % calculate gradients using a non-uniform grid via the mapped
        % pseudospectral method 
        duxdx = kgrid.dxudxn .* real(ifft(ddx_k .* shift_neg .* kappa .* fft(ux_sgx)));
        
    end    
    
    % calculate rhox at the next time step
    if ~flags.nonlinear
        
        % use linearised mass conservation equation
        rhox = pml_x .* ( pml_x .* rhox - dt .* rho0 .* duxdx );
        
    else
        
        % use nonlinear mass conservation equation (explicit calculation)
        rhox = pml_x .* ( pml_x .* rhox - dt .* (2 .* rhox + rho0) .* duxdx );
        
    end      
    
    % add in the pre-scaled pressure source term as a mass source  
    if flags.source_p >= t_index
        switch source.p_mode
            case 'dirichlet'
            
                % enforce source values as a dirichlet boundary condition
                rhox(p_source_pos_index) = source.p(p_source_sig_index, t_index);
                
            case 'additive'
            
                % extract the source values into a matrix
                source_mat = castZeros([kgrid.Nx, 1]);
                source_mat(p_source_pos_index) = source.p(p_source_sig_index, t_index);

                % apply the k-space correction
                source_mat = real(ifft(source_kappa .* fft(source_mat)));

                % add the source values to the existing field values
                % including the k-space correction
                rhox = rhox + source_mat;

            case 'additive-no-correction'
            
                % add the source values to the existing field values
                rhox(p_source_pos_index) = rhox(p_source_pos_index) + source.p(p_source_sig_index, t_index);
            
        end
    end    
    
    % equation of state
    if ~flags.nonlinear
        switch equation_of_state
            case 'lossless'
                
                % calculate p using a linear adiabatic equation of state
                p = c0.^2 .* rhox;
                
            case 'absorbing'
                
                % calculate p using a linear absorbing equation of state 
                p = c0.^2 .* (rhox ...
                     + absorb_tau .* real(ifft( absorb_nabla1 .* fft(rho0 .* duxdx) )) ...
                     - absorb_eta .* real(ifft( absorb_nabla2 .* fft(rhox) )) ...
                     );
                 
            case 'stokes'
                
                % calculate p using a linear absorbing equation of state
                % assuming alpha_power = 2
                p = c0.^2 .* (rhox + absorb_tau .* rho0 .* duxdx);
                 
        end
    else
        switch equation_of_state
            case 'lossless'
                
                % calculate p using a nonlinear adiabatic equation of state
                p = c0.^2 .* ( rhox + medium.BonA .* rhox.^2 ./ (2 .* rho0) );
                
            case 'absorbing'
                
                % calculate p using a nonlinear absorbing equation of state 
                p = c0.^2 .* ( rhox ...
                    + absorb_tau .* real(ifft( absorb_nabla1 .* fft(rho0 .* duxdx) )) ...
                    - absorb_eta .* real(ifft( absorb_nabla2 .* fft(rhox) )) ...                   
                    + medium.BonA .* rhox.^2 ./ (2 .* rho0) ...
                    );
                
            case 'stokes'
                
                % calculate p using a nonlinear absorbing equation of state
                % assuming alpha_power = 2
                p = c0.^2 .* (rhox ...
                    + absorb_tau .* rho0 .* duxdx ...
                    + medium.BonA .* rhox.^2 ./ (2 .* rho0) ...
                    );  
                
        end         
    end     
    
    % enforce initial conditions if source.p0 is defined instead of time
    % varying sources
    if t_index == 1 && flags.source_p0
    
        % add the initial pressure to rho as a mass source
        p = source.p0;
        rhox = source.p0 ./ c0.^2;
        
        % compute u(t = t1 - dt/2) based on u(dt/2) = -u(-dt/2) which
        % forces u(t = t1) = 0
        if ~flags.use_finite_difference
            
            % calculate gradient using the k-space method on a regular grid
            ux_sgx = dt .* rho0_sgx_inv .* real(ifft(ddx_k .* shift_pos .* kappa .* fft(p))) / 2;
            
        else
            switch flags.use_finite_difference
                case 2
                    
                    % calculate gradient using second-order accurate finite
                    % difference scheme (including half step forward)
                    dpdx = ([p(2:end); 0] - p) /kgrid.dx;
                    ux_sgx = dt .* rho0_sgx_inv .* dpdx / 2;
                    
                case 4
                    
                    % calculate gradient using fourth-order accurate finite
                    % difference scheme (including half step backward)
                    dpdx = ([p(3:end); 0; 0] - 27 * [p(2:end); 0] + 27 * p - [0; p(1:(end-1))]) / (24 * kgrid.dx);
                    ux_sgx = dt .* rho0_sgx_inv .* dpdx / 2;
                    
            end
        end
    end    
    
    % precompute fft of p here so p can be modified for visualisation
    p_k = fft(p);    
    
    % extract required sensor data from the pressure and particle velocity
    % fields if the number of time steps elapsed is greater than
    % sensor.record_start_index (defaults to 1) 
    if flags.use_sensor && ~flags.time_rev && (t_index >= sensor.record_start_index)
    
        % update index for data storage
        file_index = t_index - sensor.record_start_index + 1;
        
        % run sub-function to extract the required data from the acoustic
        % variables
        sensor_data = kspaceFirstOrder_extractSensorData(1, sensor_data, file_index, sensor_mask_index, flags, record, p, ux_sgx, [], []);      
        
    end

    % estimate the time to run the simulation
    if t_index == ESTIMATE_SIM_TIME_STEPS
        disp(['  estimated simulation time ' scaleTime(etime(clock, loop_start_time) * index_end / t_index) '...']);
    end      
    
    % plot data if required
    if flags.plot_sim && (rem(t_index, plot_freq) == 0 || t_index == 1 || t_index == index_end)  

        % update progress bar
        waitbar(t_index / kgrid.Nt, pbar);
        drawnow;

        % ensure p is cast as a CPU variable and remove the PML from the
        % plot if required
        if strcmp(data_cast, 'gpuArray')
            p_plot = double(gather(p(x1:x2)));
        else
            p_plot = double(p(x1:x2));  
        end
                       
        % update plot
        if flags.plot_scale_auto || flags.plot_scale_log || t_index == 1
            
            % update plot scale if set to automatic or log
            if flags.plot_scale_auto || flags.plot_scale_log
                kspaceFirstOrder_adjustPlotScale;
            end
                        
            % replace entire plot
            if ~flags.nonuniform_grid
                img_data = plot(kgrid.x(x1:x2) * scale, p_plot);
            else
                img_data = plot(kgrid.x_size * kgrid.xn(x1:x2) * scale, p_plot);
            end            
            
            % add display mask onto plot
            if ~(strcmp(display_mask, 'default') || strcmp(display_mask, 'off'))
                hold on;
                if ~flags.nonuniform_grid
                    stairs(kgrid.x(x1:x2) * scale, display_mask(x1:x2) .* (plot_scale(2) - plot_scale(1)) + plot_scale(1), 'k-');
                else
                    stairs(kgrid.xn(x1:x2) * scale, display_mask(x1:x2) .* (plot_scale(2) - plot_scale(1)) + plot_scale(1), 'k-');
                end
                hold off
            end
            
            % set plot options
            xlabel(['x-position [' prefix 'm]']);
            if ~flags.nonuniform_grid
                set(gca, 'YLim', plot_scale, 'XLim', kgrid.x([x1, x2]) * scale);      
            else
                set(gca, 'YLim', plot_scale, 'XLim', kgrid.x_size * kgrid.xn([x1, x2]) * scale);      
            end            
            
        else
            
            % just replace the y-data
            set(img_data, 'YData', p_plot);
            
        end
        
        % force plot update
        drawnow;
        
        % save movie frames if required
        if flags.record_movie

            % set background color to white
            set(gcf, 'Color', [1, 1, 1]);

            % save the movie frame
            writeVideo(video_obj, getframe(gcf));

        end
        
        % update variable used for timing variable to exclude the first
        % time step if plotting is enabled
        if t_index == 1
            loop_start_time = clock;
        end
        
    end    
end

% assign the final time reversal values
if flags.time_rev
    p(sensor_mask_index) = sensor.time_reversal_boundary_data(:, index_end + 1);
end

% update command line status
disp(['  simulation completed in ' scaleTime(toc)]);

% =========================================================================
% CLEAN UP
% =========================================================================

% clean up used figures
if flags.plot_sim
    close(img);
    close(pbar);
    drawnow;
end

% save the movie frames to disk
if flags.record_movie
    close(video_obj);
end

% save the final pressure field if in time reversal mode
if flags.time_rev
    flags.record_p_final = true;
end

% save the final acoustic pressure if required
if flags.record_p_final
    sensor_data.p_final = p(record.x1_inside:record.x2_inside);
end

% save the final particle velocity if required
if flags.record_u_final
    sensor_data.ux_final = ux_sgx(record.x1_inside:record.x2_inside);    
end

% run subscript to cast variables back to double precision if required
if flags.data_recast
    kspaceFirstOrder_dataRecast;
end

% run subscript to compute and save intensity values
if flags.use_sensor && ~flags.time_rev && (flags.record_I || flags.record_I_avg)
    kspaceFirstOrder_saveIntensity;
end

% reorder the sensor points if a binary sensor mask was used for Cartesian
% sensor mask nearest neighbour interpolation (this is performed after
% recasting as the GPU toolboxes do not all support this subscript)
if flags.use_sensor && flags.reorder_data
    kspaceFirstOrder_reorderCartData;
end

% filter the recorded time domain pressure signals if transducer filter
% parameters are given 
if flags.use_sensor && ~flags.time_rev && isfield(sensor, 'frequency_response')
    sensor_data.p = gaussianFilter(sensor_data.p, 1/kgrid.dt, sensor.frequency_response(1), sensor.frequency_response(2));
end

% reorder the sensor points if cuboid corners is used
if flags.cuboid_corners
    kspaceFirstOrder_reorderCuboidCorners;
end

if ~flags.use_sensor
    
    % if sensor is not used, return empty sensor data
    sensor_data = [];
    
elseif flags.time_rev
    
    % if computing time reversal, reassign sensor_data.p_final to
    % sensor_data
    sensor_data = sensor_data.p_final;
    
elseif ~isfield(sensor, 'record') && ~flags.cuboid_corners
    
    % if sensor.record is not given by the user, and not using a cuboid
    % sensor mask, reassign sensor_data.p to sensor_data
    sensor_data = sensor_data.p;
    
end

% update command line status
disp(['  total computation time ' scaleTime(etime(clock, start_time))]);

% switch off log
if flags.create_log
    diary off;
end